|
|
Absolute deviation, 绝对离差
) x! }7 C& W2 R" c, d9 P2 N2 [' lAbsolute number, 绝对数
+ T. @3 c" X1 ?" U$ L. f" L4 xAbsolute residuals, 绝对残差. m( _/ U; I, E1 q
Acceleration array, 加速度立体阵' h* ]# i1 o; s; ]3 l3 a" V0 @. W! S
Acceleration in an arbitrary direction, 任意方向上的加速度" j N$ G- r2 F2 V* q* `+ }
Acceleration normal, 法向加速度
' T/ E4 x' f0 }Acceleration space dimension, 加速度空间的维数) T5 V" L5 ~2 m. c1 u8 X2 v
Acceleration tangential, 切向加速度
0 M+ e9 m5 O* s; bAcceleration vector, 加速度向量
6 }& Y% k3 [1 b7 M0 x1 AAcceptable hypothesis, 可接受假设
4 e$ ?$ N; x7 S: u8 A. Q* uAccumulation, 累积4 K* r3 J1 W! o, q$ l8 a
Accuracy, 准确度! ?2 [9 U* A Y$ @! @ i
Actual frequency, 实际频数
# D) w( X6 u# e; T, j* y3 g+ q) oAdaptive estimator, 自适应估计量$ _& @* v h1 I+ q8 U2 K3 H; X
Addition, 相加' ^6 t3 ?8 e2 G# H; U' x: b) m
Addition theorem, 加法定理
3 @0 V7 `* i* D: V) HAdditivity, 可加性& A0 N; A) Y0 ~5 e. t0 X( K
Adjusted rate, 调整率; N2 Y; s0 W, X- a) L
Adjusted value, 校正值* L5 [ v w/ ~/ |4 B- P
Admissible error, 容许误差* S; [4 i& \( k7 _& `
Aggregation, 聚集性3 f7 s% ]) E" b; g
Alternative hypothesis, 备择假设
0 b& c" M" M: k _, VAmong groups, 组间
/ I/ u* D& `9 F6 |) rAmounts, 总量0 V, u9 T H, a
Analysis of correlation, 相关分析& Z3 B# h4 O( ^& R$ |4 k
Analysis of covariance, 协方差分析6 K5 R @) n( t8 n' ^
Analysis of regression, 回归分析
+ T8 j% |2 m" {4 Z+ ]- @+ _Analysis of time series, 时间序列分析- J9 B. y6 B8 X7 l" i- f" r7 w/ d
Analysis of variance, 方差分析
. t7 }0 c+ x6 ^1 n& G' f; k- u, MAngular transformation, 角转换2 m) Z8 A3 N [, _) V9 r3 n
ANOVA （analysis of variance）, 方差分析
) ] j' Q' ~3 xANOVA Models, 方差分析模型
; K: M( ^: [6 b7 tArcing, 弧/弧旋+ @' Y# q. ]$ T0 b1 U$ B. [
Arcsine transformation, 反正弦变换
0 O I- u" I! t, {0 h2 E9 E& ^Area under the curve, 曲线面积1 O- o+ U, ]: E' Z
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 ) g9 D5 t" i: Y
ARIMA, 季节和非季节性单变量模型的极大似然估计 ( f- F! u0 L/ b* ]
Arithmetic grid paper, 算术格纸
- f7 {4 H w# K- u& IArithmetic mean, 算术平均数 p" O& R1 p* Y# \* F8 i5 v
Arrhenius relation, 艾恩尼斯关系
4 @. U; a, |8 jAssessing fit, 拟合的评估 P) A1 O9 |3 F( u. ?' R
Associative laws, 结合律! V# z/ g0 @$ Z* f
Asymmetric distribution, 非对称分布( M6 s! q; _) A, ~" T) T9 d
Asymptotic bias, 渐近偏倚
* s2 z& A1 c* u% q2 M8 {. OAsymptotic efficiency, 渐近效率
8 o. B# m# A" ^8 m) j2 |( kAsymptotic variance, 渐近方差
* ~) S, d% B. Z1 H9 nAttributable risk, 归因危险度
3 ?+ @9 a$ |+ i8 e$ _Attribute data, 属性资料
& m! Y- A$ }" {- HAttribution, 属性
" Z4 Z. p; Z$ C. s: fAutocorrelation, 自相关4 J( t6 j, q) w5 Q& z
Autocorrelation of residuals, 残差的自相关
; P9 ^4 O- K: h; fAverage, 平均数& |& I: [) b1 f, g" @: T. m
Average confidence interval length, 平均置信区间长度9 T* \0 ?# o4 J' j6 O( P% M8 K7 J! f
Average growth rate, 平均增长率0 g; `6 S& x2 p' b' D! ^& I% F
Bar chart, 条形图
7 \. @# R7 m" J" Q. A( I# ABar graph, 条形图
9 s1 [. @* P4 s% F8 GBase period, 基期
: U* Z5 Y) q' N: UBayes' theorem , Bayes定理
5 Z) _7 E8 M. ~8 M$ L1 fBell-shaped curve, 钟形曲线* A R4 L* l" \. k2 p" B
Bernoulli distribution, 伯努力分布
1 R, G9 i: F4 ~4 r" sBest-trim estimator, 最好切尾估计量# C- L- w$ [1 T( H- [7 W
Bias, 偏性4 n. A3 Z8 g( Y c2 x
Binary logistic regression, 二元逻辑斯蒂回归3 H3 J. A! g7 i* E
Binomial distribution, 二项分布# j4 B8 @7 W9 E8 l6 d; J7 u5 p
Bisquare, 双平方0 {4 S* \% k+ N5 \, ~4 _2 N# }
Bivariate Correlate, 二变量相关
( Q- p% @& B7 ^0 {2 eBivariate normal distribution, 双变量正态分布+ {6 a4 [/ w# ~5 b2 n0 F& m. q4 e
Bivariate normal population, 双变量正态总体
, s# J8 y1 m4 Y DBiweight interval, 双权区间; s, q# B3 v" D7 E) @$ a! k
Biweight M-estimator, 双权M估计量6 ?6 B) A7 I# s
Block, 区组/配伍组3 C8 I' ?! W7 i) R/ {0 o, L
BMDP(Biomedical computer programs), BMDP统计软件包
$ }$ d$ X- F. P6 {& g; d0 IBoxplots, 箱线图/箱尾图 b. X/ G' |% D; U, j: S0 f# e
Breakdown bound, 崩溃界/崩溃点
' ^- k2 J2 o! F& k* {Canonical correlation, 典型相关
, Q" B2 T: S n3 j- BCaption, 纵标目
1 n$ d- z. l: \6 O. w5 n) Q3 ICase-control study, 病例对照研究
m$ a4 d( w7 d3 E1 xCategorical variable, 分类变量8 W3 s$ h% A6 _3 G" ?8 l" n
Catenary, 悬链线- d+ ?3 f# c9 E! c) u+ p' s
Cauchy distribution, 柯西分布
% Q# Z7 O* A. |: v1 U# F. n' _Cause-and-effect relationship, 因果关系
% `+ I, Y3 R6 t& yCell, 单元
0 g" p& y! T/ c5 E2 a8 w, DCensoring, 终检
% E7 h9 g' S- g* MCenter of symmetry, 对称中心
6 u) I% U2 [* A) p- QCentering and scaling, 中心化和定标* S( I1 F: m5 S
Central tendency, 集中趋势
! @1 |) F* Q4 U {Central value, 中心值( \" C* O4 y4 M* C6 p g6 O
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测1 z; y w5 L# G! [ H& r, {
Chance, 机遇; _2 j# C& Y N. W! o
Chance error, 随机误差7 y `' i8 h0 c/ R# H
Chance variable, 随机变量
9 t7 s, j& r Q" P- y9 pCharacteristic equation, 特征方程) w2 g9 g( N @+ J
Characteristic root, 特征根$ [8 i: z3 i3 z5 i" Q: m
Characteristic vector, 特征向量6 o' R; D- L# R+ ]2 V- b- F1 P* }- _) B J
Chebshev criterion of fit, 拟合的切比雪夫准则 z B6 Q* [& ]* `2 d
Chernoff faces, 切尔诺夫脸谱图& i; e, D9 n3 x: M
Chi-square test, 卡方检验/χ2检验5 I2 t# U5 H# y8 ^& Q$ ^
Choleskey decomposition, 乔洛斯基分解) x: J! L2 d P# d9 z
Circle chart, 圆图
- u8 s; r, {5 a: ?2 l/ Y L' A: KClass interval, 组距
D. G% m$ W4 Q( T6 a4 P: WClass mid-value, 组中值: J* w, q7 ~/ m/ \0 i# H% w
Class upper limit, 组上限. u: \- t8 y$ e' U. Z" P
Classified variable, 分类变量/ n/ k5 @8 j% ~; C1 ~
Cluster analysis, 聚类分析
0 {9 F# W; K0 N2 b. P2 z8 }& a {Cluster sampling, 整群抽样
0 j3 Q$ h, M4 ^% f0 [' G9 _Code, 代码; v5 c( ]9 h6 l' M
Coded data, 编码数据
3 o& \( {' n: nCoding, 编码) O5 X* S/ F' b }% j( [
Coefficient of contingency, 列联系数
6 ^1 o* ~3 f' X$ i3 I+ mCoefficient of determination, 决定系数& Y% I' P3 I/ I4 |2 [+ q/ i
Coefficient of multiple correlation, 多重相关系数
% Y, w8 M4 j7 nCoefficient of partial correlation, 偏相关系数
3 k) Q/ v* v. U( q) P+ _( z w$ ZCoefficient of production-moment correlation, 积差相关系数
0 T$ b. C9 n& f1 tCoefficient of rank correlation, 等级相关系数$ q, u6 p" y7 v* j" D& g/ Y
Coefficient of regression, 回归系数0 Y U; x6 f4 b9 b0 v
Coefficient of skewness, 偏度系数
5 @1 v3 I3 M- \. y: _Coefficient of variation, 变异系数
' v/ j1 X0 k- D7 c& v4 pCohort study, 队列研究
; e) B! z" T; C, t7 ~# q: aColumn, 列
7 K4 S7 r8 D7 Q& ^! l/ p5 {. dColumn effect, 列效应
$ v5 i" H1 O. r! wColumn factor, 列因素7 [+ n8 C4 d5 `& O& s# U9 Q; `( r
Combination pool, 合并
8 i4 @3 Q4 q0 MCombinative table, 组合表. ~3 T* k1 x% x* L: N3 S* Q
Common factor, 共性因子
7 b6 u5 Y1 R* ~# ]( {Common regression coefficient, 公共回归系数
+ S1 t. d/ P- M* R$ {Common value, 共同值& l2 _6 i4 _1 H! _6 i
Common variance, 公共方差 ~, h5 B5 f/ V5 k0 d
Common variation, 公共变异) _" o- Y" g s
Communality variance, 共性方差5 B0 p$ @/ C. ]
Comparability, 可比性
- V, o) a0 A- jComparison of bathes, 批比较
+ u0 I- v0 [/ W5 O( Z' k! U; LComparison value, 比较值
3 @0 f0 E: O2 S1 u, mCompartment model, 分部模型3 {' C8 f% ]" U8 m- J
Compassion, 伸缩
4 m8 E8 y. [. JComplement of an event, 补事件
0 J8 U+ \8 M0 p' B: b& W; J! ?Complete association, 完全正相关
8 S' _3 g- h8 y: w wComplete dissociation, 完全不相关8 k* b; x) B+ F. Z. Y n0 y8 S: Y
Complete statistics, 完备统计量
% M' M& Y u$ V& W- iCompletely randomized design, 完全随机化设计
' m+ k5 C) v' z' Q2 a$ a1 e" DComposite event, 联合事件3 f; P- _2 P! X1 ?$ R
Composite events, 复合事件0 \/ q" l' ~! I1 Q b0 ^ d+ D
Concavity, 凹性3 U7 ~, ~3 [3 `2 Y
Conditional expectation, 条件期望
! D9 M8 w @+ F9 M' |( zConditional likelihood, 条件似然+ V4 H& m/ B% t' f
Conditional probability, 条件概率
2 V! P5 i8 U! j% C; @/ E) N* JConditionally linear, 依条件线性 u+ `" R. a/ t' Y8 b
Confidence interval, 置信区间8 T, m- @7 V# p% D R7 o( h1 ?
Confidence limit, 置信限: e# i* x6 @! Y! O9 L
Confidence lower limit, 置信下限- K9 k7 [9 \, s# _# v
Confidence upper limit, 置信上限" d% m9 e" g- C( u! I2 n S; i7 ^
Confirmatory Factor Analysis , 验证性因子分析
h, v8 _7 g5 O, Z# OConfirmatory research, 证实性实验研究
5 d) m, O* u1 u# MConfounding factor, 混杂因素* o8 L: E1 D4 o
Conjoint, 联合分析7 @: Z: D, g9 j4 s8 v4 [
Consistency, 相合性
5 u2 v: v* {0 d [3 `+ wConsistency check, 一致性检验
0 D( I5 m: _) u% h. ^2 _4 {7 `! sConsistent asymptotically normal estimate, 相合渐近正态估计
% Q8 v; N5 K& M" C$ s! j; cConsistent estimate, 相合估计
* L, @8 s8 M( J* Q9 v# tConstrained nonlinear regression, 受约束非线性回归
0 U( @9 Z: a* n* l! B6 y* qConstraint, 约束; P( o+ N4 ]) t: m: f! Y' X& E
Contaminated distribution, 污染分布0 _7 f2 c9 R% d; k+ \
Contaminated Gausssian, 污染高斯分布) z' ` o+ [- z+ y) d! ]# w
Contaminated normal distribution, 污染正态分布
$ H5 O6 A- @- W: A7 l) {Contamination, 污染
x0 o0 i1 U, W2 u2 [( q$ Y! i# ^Contamination model, 污染模型$ f7 J+ d/ Q1 m/ D( \3 b* p
Contingency table, 列联表9 G2 C2 ~+ m: S6 P
Contour, 边界线
/ s c/ G- M* e: r% B2 ?# {Contribution rate, 贡献率
F" `, p+ k1 L! ^8 B; @# TControl, 对照7 z V, {! L- A+ @9 e
Controlled experiments, 对照实验
3 m- v6 r' z7 e6 o" y% E e% ]; f# Y% \! FConventional depth, 常规深度
" u, k0 V+ P0 ^# ~2 r" wConvolution, 卷积
9 K# Z$ b j( a! ?Corrected factor, 校正因子* [* A N b c/ T8 }9 a
Corrected mean, 校正均值: c. m" H* b; i3 E) [7 l* Y, u
Correction coefficient, 校正系数
( W2 Y- M$ K N& e+ v) }) r0 FCorrectness, 正确性! V, ]5 ?, z0 K6 G; V7 K5 h! f
Correlation coefficient, 相关系数
5 P/ H8 R" Y% z6 R2 E$ BCorrelation index, 相关指数
! `4 ]5 |: s5 l8 oCorrespondence, 对应
5 s3 v* E0 r3 HCounting, 计数
! f* v+ u s7 y8 Y* vCounts, 计数/频数
- {; }& P% ^6 o5 }Covariance, 协方差
/ Q; t% i& @ [, g: }9 B- H5 FCovariant, 共变 ) B% ?* G8 M; h7 u z! A. S
Cox Regression, Cox回归
7 W& a2 V/ ^: J/ f, U- YCriteria for fitting, 拟合准则
2 j# T& [' n' uCriteria of least squares, 最小二乘准则
$ A/ r! E' U: s8 OCritical ratio, 临界比" c6 e7 B0 ^+ N4 ~" ^
Critical region, 拒绝域
0 ^$ ], D; ~8 \7 [" JCritical value, 临界值
" r/ |0 N/ n8 g- kCross-over design, 交叉设计
1 O9 o$ _4 c) f5 ECross-section analysis, 横断面分析
" ~# A2 F+ N: ?% rCross-section survey, 横断面调查
+ z: o; I+ Q1 o0 S: |5 l; CCrosstabs , 交叉表 8 @. F/ r& c. p+ b
Cross-tabulation table, 复合表9 l/ J+ F& y1 s0 h! u
Cube root, 立方根
* j9 I) ^8 O6 V/ E: w4 d& pCumulative distribution function, 分布函数
) B* R& s% X( \Cumulative probability, 累计概率9 z* s# }+ j' ^7 ^
Curvature, 曲率/弯曲
8 B: m3 t( t; r( [Curvature, 曲率
2 J! R- [% _( \% R9 W; K/ J& @8 SCurve fit , 曲线拟和 : s8 j; H9 m, `4 r# o0 z; q Z
Curve fitting, 曲线拟合9 B$ u. Q9 i& {; ?) b5 a. b6 ]. q) p/ S
Curvilinear regression, 曲线回归/ M1 t3 R8 p6 c& \
Curvilinear relation, 曲线关系- E" g+ W. o4 C8 D: M
Cut-and-try method, 尝试法. _* n5 a+ M4 e5 k0 {- D3 }# K$ J
Cycle, 周期+ V5 u v; v( R( v+ c; d P! M1 e
Cyclist, 周期性
- F/ k* _$ ^) r: B0 U* {D test, D检验0 R8 v9 {1 I& J( P/ X
Data acquisition, 资料收集9 [6 `' p* h8 e/ `
Data bank, 数据库+ c0 F. Y- \+ m* |; W& g4 |6 i
Data capacity, 数据容量+ @8 q# @, C0 l' p
Data deficiencies, 数据缺乏
# `0 L* W7 g4 C6 wData handling, 数据处理
6 \9 ~/ N$ U' nData manipulation, 数据处理; W+ }* ~: u% J# }
Data processing, 数据处理
; ^0 n6 v( O! ` s: OData reduction, 数据缩减
b2 k' q1 i5 ]" ]3 q9 n1 O+ @' E7 b YData set, 数据集
/ O$ o% P2 k& gData sources, 数据来源) D8 }+ U* z ], }8 t0 h9 u3 A
Data transformation, 数据变换
% E0 u, Q) c* g( k. X2 k* \7 BData validity, 数据有效性
/ c3 y7 r, d# U, W' T# n% Q9 @+ x. {Data-in, 数据输入
, I8 q6 f# o9 i0 G0 H ~; cData-out, 数据输出( K; Y0 u1 E; `( q7 H% ] t
Dead time, 停滞期9 \1 S- v& w" l1 o7 b8 o$ B
Degree of freedom, 自由度
9 x0 v2 c' U9 m3 E. KDegree of precision, 精密度
+ N! {: _+ q7 _6 J( Z0 B& F BDegree of reliability, 可靠性程度7 v' K& m0 d/ E0 i: x
Degression, 递减
' x/ y: D! |6 G8 |Density function, 密度函数
0 w H+ x3 e. U: W3 cDensity of data points, 数据点的密度
! \6 ]& J+ a: s: ]Dependent variable, 应变量/依变量/因变量
7 j. y8 q3 R+ n4 TDependent variable, 因变量/ a5 {" m1 u, O: H( [7 \& D
Depth, 深度* X6 j) X' U# ^- Z* n
Derivative matrix, 导数矩阵
2 F% a. [+ V; YDerivative-free methods, 无导数方法, R( U, [. Q7 v$ q
Design, 设计. f0 R" h2 O- e" m8 f/ ~
Determinacy, 确定性
. k6 |: V4 x* FDeterminant, 行列式
; `) {/ F. V/ @$ \1 m( q2 T, FDeterminant, 决定因素
2 Y$ W$ M- C. [ M/ TDeviation, 离差
1 B0 Q, U7 i6 D* aDeviation from average, 离均差5 O* E; X' S9 C6 _5 T4 V8 U* B
Diagnostic plot, 诊断图
4 _2 R7 V* Y- x- [Dichotomous variable, 二分变量" w3 L8 }# a% c
Differential equation, 微分方程
( v1 S. z i6 \# P& zDirect standardization, 直接标准化法
6 {4 c$ T" I d' zDiscrete variable, 离散型变量
+ K5 J8 z4 ?/ fDISCRIMINANT, 判断
$ f. t! _) J/ ~: j0 T+ k2 QDiscriminant analysis, 判别分析 y" n3 S# \$ X, Y; q+ S
Discriminant coefficient, 判别系数
- V$ o5 B1 j3 Y5 E% h. H6 ~Discriminant function, 判别值. b6 ^- |" ]) t
Dispersion, 散布/分散度
* `1 I7 Q7 r/ T! YDisproportional, 不成比例的
3 M$ L) Z+ m" gDisproportionate sub-class numbers, 不成比例次级组含量
r% n$ d/ a* _. z! n1 v& IDistribution free, 分布无关性/免分布8 k4 g7 G$ b/ H3 Z7 ?& ^+ K
Distribution shape, 分布形状+ T: q/ J0 t. ]7 o5 c8 r
Distribution-free method, 任意分布法: @& u+ g: P+ @# C' ?
Distributive laws, 分配律2 n3 s# x! ?/ ]$ r! E
Disturbance, 随机扰动项
1 o3 s0 }$ R! B- C( v( ^Dose response curve, 剂量反应曲线; f- A1 \# A# a2 S/ h" i- \0 U2 T
Double blind method, 双盲法
4 j7 k: b+ F- t7 EDouble blind trial, 双盲试验
" B) q8 E8 p% WDouble exponential distribution, 双指数分布; T; Y: O# D0 ?* } v
Double logarithmic, 双对数
) R1 a% d3 s& N" n1 h3 o0 O" [) QDownward rank, 降秩0 Q: P ?; d4 J
Dual-space plot, 对偶空间图8 Q8 u& z+ {- P7 j3 M' _5 T
DUD, 无导数方法7 I4 r! {% g- r2 M
Duncan's new multiple range method, 新复极差法/Duncan新法
( m, M& X T! Z8 a# d: H+ CEffect, 实验效应
4 @" b* ~7 t6 `, o5 ~ BEigenvalue, 特征值
8 p1 P2 i' Z% E3 cEigenvector, 特征向量# P+ M \# u9 j% a, B9 _
Ellipse, 椭圆
9 K, a3 ]2 t& HEmpirical distribution, 经验分布8 |: u( h3 h2 i
Empirical probability, 经验概率单位; z* n1 i( r( a
Enumeration data, 计数资料% g2 Y1 |$ N0 J& i
Equal sun-class number, 相等次级组含量
8 y) D/ _7 q& A2 Z# [9 wEqually likely, 等可能
" [. Q1 k+ P% ~' v8 C- z: T+ |Equivariance, 同变性
( p$ W" M [+ {5 N" F2 M' LError, 误差/错误
1 A; q' ~ W4 dError of estimate, 估计误差
2 ?" O$ S2 q& HError type I, 第一类错误
4 s' V( ]* |1 S# _4 h4 x4 I+ VError type II, 第二类错误
1 @2 m8 ?2 U7 {( W( g0 wEstimand, 被估量# Y# I. y; x6 R. X6 [ j# G
Estimated error mean squares, 估计误差均方% L. \) ^5 d) v- s6 F. {
Estimated error sum of squares, 估计误差平方和# c2 T# O k5 ^2 h
Euclidean distance, 欧式距离) c; ?# R) t% Q! }9 {% Q! ~+ ~
Event, 事件
$ P/ |& d5 k5 F, s& f0 l) pEvent, 事件
8 _+ v7 s- _' j2 h4 U8 G# z( n4 AExceptional data point, 异常数据点. F- q' a& M8 p3 U
Expectation plane, 期望平面" q/ ~4 A+ y2 H. P
Expectation surface, 期望曲面
1 }6 X# \/ l1 {8 R9 |1 q* |! |) IExpected values, 期望值3 `* q7 Y2 r: a6 L9 W
Experiment, 实验
: k5 T5 Y1 R }; Y) \: r; `9 p' AExperimental sampling, 试验抽样
: T6 P1 { [ zExperimental unit, 试验单位
/ P5 a6 A- o( V( Y* i. ~/ RExplanatory variable, 说明变量9 A& d' W) F/ Q$ C4 C* E7 V
Exploratory data analysis, 探索性数据分析
- p$ W* s+ c: J/ J, ~0 a9 nExplore Summarize, 探索-摘要
8 X! D& E8 Q2 b+ XExponential curve, 指数曲线
& c& H3 ?5 Z+ [/ D# H4 gExponential growth, 指数式增长
5 ]- m6 K6 @ ^EXSMOOTH, 指数平滑方法
+ d5 G+ g2 ]" x! @Extended fit, 扩充拟合
! c' g8 T4 S+ p, v4 C3 B {Extra parameter, 附加参数9 d: _0 V! M% p
Extrapolation, 外推法
" S: H* w! P$ Z# ]Extreme observation, 末端观测值' d3 L' [) i4 Y
Extremes, 极端值/极值
2 b# D; ~' Y& v* t& E2 ^F distribution, F分布/ X" G9 R0 _+ s8 C" K
F test, F检验9 I! S1 O9 @! p/ a$ p- r) N4 t4 W
Factor, 因素/因子
8 H/ y @. z2 e) p1 e: r: BFactor analysis, 因子分析
7 D( O1 m D% [% B& sFactor Analysis, 因子分析, r1 U; J2 P3 u
Factor score, 因子得分 2 H: Q) }# ~0 X
Factorial, 阶乘
4 O9 D. V/ k* Q3 h; SFactorial design, 析因试验设计
) t6 g. h9 h! J6 G D, U" g0 qFalse negative, 假阴性! k$ _+ T9 E( q* y8 n. b
False negative error, 假阴性错误
" L8 ~, e, M+ S% ?$ m- p8 rFamily of distributions, 分布族* e2 o) J! L/ v3 h
Family of estimators, 估计量族0 s9 S/ p z _& y
Fanning, 扇面
1 V0 l6 u4 O$ v; rFatality rate, 病死率7 q5 M) `/ t; }! I
Field investigation, 现场调查
' U+ f2 s) a" j% Q2 q5 C- N6 IField survey, 现场调查
. ~+ ]7 p" L' G* } vFinite population, 有限总体
& q& j, @# C7 a! oFinite-sample, 有限样本
$ B0 Z, `) v# q' p& K/ c% o% Q0 IFirst derivative, 一阶导数, t- E3 E# g' A |) K5 n8 k" P$ ~
First principal component, 第一主成分+ \2 e& [ R1 o% [. j
First quartile, 第一四分位数# U* G+ S+ o1 E Z
Fisher information, 费雪信息量
) X1 A0 k% _( T9 E. G9 U5 k7 wFitted value, 拟合值
- A8 |6 c& h2 V" p5 D7 l- {, W7 X, {Fitting a curve, 曲线拟合
" a% E* a( s" D) r% lFixed base, 定基) l; y& q9 k7 W4 `$ S
Fluctuation, 随机起伏3 j& x6 y4 W4 ^& K* L
Forecast, 预测4 k+ E9 P; E4 u
Four fold table, 四格表# G$ y; p. r0 q: C+ \, \
Fourth, 四分点
6 v v/ p* I- z; L% t; jFraction blow, 左侧比率( k0 L4 H' E; K$ H/ a% e
Fractional error, 相对误差) X' E* p% K7 t1 y) u( C
Frequency, 频率1 c K( O( v& o, V
Frequency polygon, 频数多边图
' q f6 Q5 J8 ]0 h. QFrontier point, 界限点
* _- E" w6 z9 C8 ]/ ^: u4 g! CFunction relationship, 泛函关系
* {) P0 k0 y: e8 G A3 f9 PGamma distribution, 伽玛分布 D6 Y+ [( Z& D, S
Gauss increment, 高斯增量8 r: t7 h$ [9 z9 C' K* _8 H# g
Gaussian distribution, 高斯分布/正态分布
3 I- G( { ^/ g D9 ZGauss-Newton increment, 高斯-牛顿增量
0 z: y. f6 X% w$ BGeneral census, 全面普查
# b) ~' c' A) {GENLOG (Generalized liner models), 广义线性模型
, w2 E8 U4 m; y" eGeometric mean, 几何平均数
- i4 _( Q" _2 O/ q1 k, {" T4 LGini's mean difference, 基尼均差
0 j1 Q7 j. C; t0 p: mGLM (General liner models), 一般线性模型 % g( c/ Q, l9 t
Goodness of fit, 拟和优度/配合度+ ^0 A: D5 J* ?
Gradient of determinant, 行列式的梯度! m9 {- y4 ?2 Z3 V Y8 N6 G
Graeco-Latin square, 希腊拉丁方
/ E' x, O- g( F% D4 @- BGrand mean, 总均值
7 Z) p1 V/ J+ tGross errors, 重大错误
# R* F# m- r( K9 ^+ X4 ^) ]6 o' O( |Gross-error sensitivity, 大错敏感度9 L" s, K+ L$ m: @( S3 N
Group averages, 分组平均
6 T5 z/ b8 J* r' @: j$ W, ?Grouped data, 分组资料- ^2 L0 X7 U/ V% E
Guessed mean, 假定平均数! p- |, A; S5 I
Half-life, 半衰期. |: r T1 v; P( ^) q5 V
Hampel M-estimators, 汉佩尔M估计量
6 g8 U% ^3 q9 X' m1 QHappenstance, 偶然事件
; e) P4 T4 a8 D+ _$ q$ ]- f1 `/ vHarmonic mean, 调和均数# Q* {, `* x& g$ t" M \
Hazard function, 风险均数6 F5 P& E6 { ^. f V0 I
Hazard rate, 风险率
2 O- O/ h. u9 z: lHeading, 标目 & i2 B# b8 w) p& F
Heavy-tailed distribution, 重尾分布
$ t3 e- z$ m+ c# yHessian array, 海森立体阵
% u6 b# A9 y6 G: N% ]Heterogeneity, 不同质 C# G# g- H; N' c5 g0 E$ z
Heterogeneity of variance, 方差不齐 " l F0 ~. x7 f; ?2 q
Hierarchical classification, 组内分组* d5 E' l& t4 \/ \. T6 {' X1 Z
Hierarchical clustering method, 系统聚类法
" V# G, t* a- u5 T! |3 yHigh-leverage point, 高杠杆率点- M. E& e/ D+ h( V/ }# u0 \1 O
HILOGLINEAR, 多维列联表的层次对数线性模型) \& s& h" |0 n! F5 Z2 L1 P
Hinge, 折叶点
& p: y" H, x3 v, U, MHistogram, 直方图
3 E8 N* @' K6 Y$ _+ vHistorical cohort study, 历史性队列研究 ( d6 `" |: f& b1 k
Holes, 空洞2 a% Z# O% A9 I$ t
HOMALS, 多重响应分析
2 l2 `6 m* M) }, E0 O5 c ]Homogeneity of variance, 方差齐性
\/ u+ C. J4 I! Y# s2 E2 VHomogeneity test, 齐性检验
1 ?0 A3 M' K; t! A. mHuber M-estimators, 休伯M估计量5 A9 A+ r) s f$ V" j
Hyperbola, 双曲线( o7 b' J; D$ s& Q! I* }3 ~
Hypothesis testing, 假设检验
, r7 N) i% y5 Y7 C) I# z1 ?% j2 ]Hypothetical universe, 假设总体
# f6 A( s: C2 U4 ` j8 kImpossible event, 不可能事件4 G+ G0 U, G+ ?( t7 {6 c
Independence, 独立性
% O: w; A8 |$ M' D$ _8 xIndependent variable, 自变量
4 t( v- w y& e# P/ BIndex, 指标/指数
1 v+ H0 q' v6 ?" `- x! v# }. RIndirect standardization, 间接标准化法* p0 n3 O7 M7 `6 q: \& m
Individual, 个体
' y4 y' H: j! q! C$ j- kInference band, 推断带
b; Q6 P! O' I' k- I/ r- d% lInfinite population, 无限总体
' a2 X- X e; l5 G% xInfinitely great, 无穷大
4 Z! E- {3 W, I4 yInfinitely small, 无穷小8 V: G7 ~+ h1 L5 x& h7 k8 |
Influence curve, 影响曲线
- W* x7 g- }7 P7 r$ SInformation capacity, 信息容量
. C3 @" q% n& kInitial condition, 初始条件/ Q! K% b& |5 v; m9 z% Q
Initial estimate, 初始估计值0 j8 S/ O0 v* @ ~
Initial level, 最初水平
0 @, u7 o0 B3 W) n: h& I. n" W6 a9 Z9 bInteraction, 交互作用
+ w8 V1 q$ }$ ] }Interaction terms, 交互作用项
7 d. J7 K$ N: ]+ nIntercept, 截距
; i: j8 H' Q% E" \) KInterpolation, 内插法
! @# _$ d6 Q* [3 U# cInterquartile range, 四分位距
* M# f) ^9 `# ~9 \$ j$ DInterval estimation, 区间估计" j* T1 D, ]* M1 p/ s1 `( ?7 ^
Intervals of equal probability, 等概率区间/ [7 H. H, ^) w$ v
Intrinsic curvature, 固有曲率
: N {" B) e: a2 ?' B5 q$ s, pInvariance, 不变性8 v" R* u9 ~ z# l! G$ z
Inverse matrix, 逆矩阵
$ @. K" p1 a' n# b: X& j7 y2 xInverse probability, 逆概率
9 P' z# y( Z \) u! q2 T- d, Z9 S. \Inverse sine transformation, 反正弦变换. f. n; U4 b* u# s
Iteration, 迭代
) H& `2 @0 C4 CJacobian determinant, 雅可比行列式, Y) F6 x" B+ K0 |
Joint distribution function, 分布函数
2 r- p5 N6 i! |+ ^Joint probability, 联合概率+ D. [) V1 \6 D! ~
Joint probability distribution, 联合概率分布
. z2 N0 s$ y/ m5 @K means method, 逐步聚类法; q" N& H8 h' z3 f1 q
Kaplan-Meier, 评估事件的时间长度
7 a5 J4 @+ f# w4 k5 B5 \Kaplan-Merier chart, Kaplan-Merier图
. t4 ]) P# b, B! E) IKendall's rank correlation, Kendall等级相关: a( N- q* M( z9 v/ b2 q
Kinetic, 动力学- `2 P S+ a, A7 _
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 G" K M; ]' W8 KKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
6 c6 l$ c- u1 g4 V, Z1 TKurtosis, 峰度
# K0 T+ a; o: \$ @Lack of fit, 失拟, Y v, D7 w7 S( o
Ladder of powers, 幂阶梯2 z# [! Z5 m3 O* O, j3 T& P
Lag, 滞后
y4 L9 |: L* @Large sample, 大样本/ O3 K% s) h. \* ]9 Q9 T
Large sample test, 大样本检验
, @5 ^" t: K8 t Y KLatin square, 拉丁方0 @# X* ]6 y! r) l
Latin square design, 拉丁方设计
0 }5 U2 ] I3 h9 [# L+ v7 {0 `7 ^Leakage, 泄漏
8 n3 H) z. A3 J! x! XLeast favorable configuration, 最不利构形
9 O2 M. X6 U. I: p* t6 V" |Least favorable distribution, 最不利分布4 H% X* d$ ^! z) y
Least significant difference, 最小显著差法
6 d' Y) o) h7 p) I% w1 g4 B" tLeast square method, 最小二乘法
5 [; x W9 Z- \Least-absolute-residuals estimates, 最小绝对残差估计
& V9 T9 i" o$ |4 ^+ h q7 f5 wLeast-absolute-residuals fit, 最小绝对残差拟合
0 O& [) n2 n( j. H& W) j9 T$ \) WLeast-absolute-residuals line, 最小绝对残差线
0 s. }4 \4 o& E7 k2 ^* L' q# z0 cLegend, 图例5 q/ t0 y. ?8 B+ t1 I- b
L-estimator, L估计量7 K; Q. o' m+ W, k
L-estimator of location, 位置L估计量
! f, @" ]& B/ ^) U0 t# JL-estimator of scale, 尺度L估计量
0 C* e2 Q, v4 E [% J1 C2 dLevel, 水平
4 ]) F6 b0 L* J( l P7 @Life expectance, 预期期望寿命0 k* g% K) u1 H% `& |% L
Life table, 寿命表
& t4 \. ^- C4 V. e7 W4 GLife table method, 生命表法4 o; o: G3 ^2 O! S8 X1 C
Light-tailed distribution, 轻尾分布: \3 R% w9 c6 [* G0 [" }/ E
Likelihood function, 似然函数& |8 N0 x* V+ d; @7 Q' B. V
Likelihood ratio, 似然比
5 `! e1 v- d" Oline graph, 线图
7 \9 _# f6 S) T4 D1 tLinear correlation, 直线相关
3 ~) y9 S0 i( u$ q# PLinear equation, 线性方程% @6 c" H3 u4 d# X+ Q: P; \
Linear programming, 线性规划. b+ `5 t1 j( B( p' G' y- l
Linear regression, 直线回归( U W9 S9 W2 c" {' X6 K
Linear Regression, 线性回归. H2 c. Z6 Z- _; D4 D, ~7 O7 _& `
Linear trend, 线性趋势
& E3 F) A3 y2 A) R) _" D8 W5 w ?Loading, 载荷
' |. ?+ W0 ~3 v4 W5 A* o0 wLocation and scale equivariance, 位置尺度同变性
, C, L. [+ b: c7 i8 w1 e2 c qLocation equivariance, 位置同变性
) h- ~1 d0 A5 K7 \. qLocation invariance, 位置不变性
: h- C2 w& |( A# b5 |3 _( ` XLocation scale family, 位置尺度族$ D6 v! U+ r; L0 b* |3 i
Log rank test, 时序检验
: H- N7 I, J) a9 F1 ILogarithmic curve, 对数曲线
5 t: m9 k! R) NLogarithmic normal distribution, 对数正态分布
6 f% V i# F8 `2 h+ o2 t9 CLogarithmic scale, 对数尺度; a0 B9 u4 u" ?# }3 e
Logarithmic transformation, 对数变换
^3 o8 }0 B W: HLogic check, 逻辑检查: F7 H8 Y1 g# j2 L
Logistic distribution, 逻辑斯特分布% S+ ?+ {9 w9 X; t
Logit transformation, Logit转换# U( u4 h8 T' x1 F% u7 q5 l
LOGLINEAR, 多维列联表通用模型 * R! J3 g! r7 m) M
Lognormal distribution, 对数正态分布" J4 w" }$ Z! ]1 P4 C
Lost function, 损失函数1 t0 {- e; \7 }8 u9 z+ g8 k" M
Low correlation, 低度相关
) J4 ]! j% B, f5 M5 _# LLower limit, 下限' a) |' H8 u8 _1 u, g
Lowest-attained variance, 最小可达方差3 _; E/ q6 ^0 H5 V% w# F
LSD, 最小显著差法的简称( r# F8 K2 n F# i
Lurking variable, 潜在变量
$ r$ Z3 C7 f! j3 D; J9 T4 V4 UMain effect, 主效应2 U2 j0 J2 J9 ]
Major heading, 主辞标目' m+ T! \$ p" {1 p4 d
Marginal density function, 边缘密度函数$ |0 |$ n7 m Q% x; G" u
Marginal probability, 边缘概率6 D& F4 t& s, m8 x: Z9 N: }
Marginal probability distribution, 边缘概率分布9 j& H' o* E+ v" v0 q
Matched data, 配对资料
3 N2 @3 H4 Q4 Y6 D- nMatched distribution, 匹配过分布
0 m* r T0 f0 z' YMatching of distribution, 分布的匹配
5 r7 l+ @/ X# K5 ^! Z; g& uMatching of transformation, 变换的匹配
' ~- P6 M# f1 o0 D, M4 a' s. x! aMathematical expectation, 数学期望 j3 F/ ]4 W2 h
Mathematical model, 数学模型
" Z6 {' ]5 \8 PMaximum L-estimator, 极大极小L 估计量
0 O2 J; z: O3 d! n' w" xMaximum likelihood method, 最大似然法1 W% E# u+ |, I7 _' b* q+ a7 J* @
Mean, 均数/ h+ i/ J- H. d, y
Mean squares between groups, 组间均方
1 g( f) W# T9 b N* aMean squares within group, 组内均方 m9 v( s, d6 q- S
Means (Compare means), 均值-均值比较1 p2 A% K& q6 s* S; b
Median, 中位数. |, |9 W) H5 U( q
Median effective dose, 半数效量6 \& j/ y+ d8 m6 M7 }
Median lethal dose, 半数致死量
8 T& H( k- C. c/ z7 Z! SMedian polish, 中位数平滑8 K' M# }% K: P% k
Median test, 中位数检验
8 B, l# @0 b2 m( {4 z' {( xMinimal sufficient statistic, 最小充分统计量
# O4 @% O2 Q o' R; EMinimum distance estimation, 最小距离估计* Y0 ]+ i+ d. L6 l
Minimum effective dose, 最小有效量# D- G5 ?9 }2 O2 f7 W$ A
Minimum lethal dose, 最小致死量
% f7 R* N3 Z) P) FMinimum variance estimator, 最小方差估计量, T# T7 ^8 k4 E; S* {
MINITAB, 统计软件包3 A6 L. }; y: {
Minor heading, 宾词标目, n+ y9 y% T. l- j i
Missing data, 缺失值
I- M" c) m* C# @Model specification, 模型的确定
' R& y+ O& S! g. W6 h: w1 _" r- GModeling Statistics , 模型统计% g! `- q% m& _* ]
Models for outliers, 离群值模型0 O4 j( C+ z9 b" J' g" B) H
Modifying the model, 模型的修正
% a9 G, V* C8 o; s/ jModulus of continuity, 连续性模- B+ g7 y) L' B
Morbidity, 发病率
$ [9 _; m! J9 U. iMost favorable configuration, 最有利构形! M0 I+ s, g! \1 k
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
7 _2 z# W3 S9 d( WMultinomial Logistic Regression , 多项逻辑斯蒂回归
3 u. X) o8 u) |* A) J: W+ Z! v& j9 pMultiple comparison, 多重比较
% E6 u, G4 S& w5 I% d" e* y4 kMultiple correlation , 复相关
: `& H3 q3 [% m: h! m9 P6 @% i5 ^- ]Multiple covariance, 多元协方差6 b" R" |8 h5 M* l& j# F2 {
Multiple linear regression, 多元线性回归. ~$ R8 O M `6 G4 k
Multiple response , 多重选项3 y! z! N2 K; H$ Z+ c5 d7 p
Multiple solutions, 多解, ^4 D3 l+ Y( O% J5 j
Multiplication theorem, 乘法定理% Z8 M) E3 }$ @5 c3 p7 F) d( M5 o
Multiresponse, 多元响应( O, [" g" ^( O$ T1 p( J
Multi-stage sampling, 多阶段抽样4 B1 b, ^# N" y% p- L o1 h; S- _; E
Multivariate T distribution, 多元T分布
+ d& P- Z! H0 b' e7 J" tMutual exclusive, 互不相容
$ P6 }- q) D! |. t! C7 c pMutual independence, 互相独立
% M, A. t3 N- W, o9 M6 o GNatural boundary, 自然边界3 A9 e7 r) O" s' Y2 J0 ^
Natural dead, 自然死亡
3 T. ?" b- z( ?0 uNatural zero, 自然零
3 h( g: o; T& O: w m; WNegative correlation, 负相关
R9 s; Z) D1 Q. {! X8 r4 KNegative linear correlation, 负线性相关
0 \# V7 @$ d" |1 ENegatively skewed, 负偏
, W+ k& |! q8 `6 z8 iNewman-Keuls method, q检验
$ j6 b m( ]- \& v- iNK method, q检验9 C: n) G( V1 C. |! H# F5 g
No statistical significance, 无统计意义
# p) t% M: a3 jNominal variable, 名义变量
0 S, j9 n% y5 o% d7 {+ `$ \Nonconstancy of variability, 变异的非定常性
$ ?9 W9 }3 ]' Z# ]1 m/ MNonlinear regression, 非线性相关
4 D$ ~1 B9 ?+ b0 i) |0 QNonparametric statistics, 非参数统计
9 R. a" s/ g- `" d8 eNonparametric test, 非参数检验
$ S0 R1 O+ \8 x2 MNonparametric tests, 非参数检验2 ]" T9 a) {( |- f& }: }; c/ U, ~
Normal deviate, 正态离差+ C T; b% W0 o' L7 G
Normal distribution, 正态分布
6 q# _# t; Z5 DNormal equation, 正规方程组; Q; {, I4 z+ o9 K
Normal ranges, 正常范围
2 z+ B1 ^3 q- Z" k) KNormal value, 正常值
! I g% Y9 u2 s+ Z! z( z1 XNuisance parameter, 多余参数/讨厌参数
, r( f0 i6 x8 X a- {Null hypothesis, 无效假设 ( H! E6 h) L; M0 V7 g
Numerical variable, 数值变量
0 q- w1 s* d5 R1 gObjective function, 目标函数
9 a) ]# [1 ?5 B1 P+ `& F' IObservation unit, 观察单位2 t7 j% _+ Y8 b' t& z# `. H
Observed value, 观察值
4 u- a( \) P/ C" n) f5 iOne sided test, 单侧检验
* [. x" {1 u( [: Z+ @One-way analysis of variance, 单因素方差分析, \& G- C' K9 [5 z) h- }- C
Oneway ANOVA , 单因素方差分析4 @0 q4 H( E: [
Open sequential trial, 开放型序贯设计7 Q$ U' ^! \. o8 [/ ?( c
Optrim, 优切尾 L b4 E' A/ ]3 M* R0 C& l
Optrim efficiency, 优切尾效率2 t; `4 ?( F- c
Order statistics, 顺序统计量
2 f; q7 d; u4 ZOrdered categories, 有序分类
- e* b0 D# D3 U7 K# j3 E6 F. EOrdinal logistic regression , 序数逻辑斯蒂回归
5 a+ l5 K. T4 g1 C9 A) |Ordinal variable, 有序变量( Y3 J+ G# [2 T, \8 [
Orthogonal basis, 正交基
* ^* j; |8 `' \$ s! y- ^( YOrthogonal design, 正交试验设计
2 ^* K- F" B- c8 X7 [; ~Orthogonality conditions, 正交条件( t2 t( @2 A' @2 `) r$ `
ORTHOPLAN, 正交设计
1 @; m1 M8 M1 q0 k+ d5 a0 ~Outlier cutoffs, 离群值截断点
& [# E6 t& z. w" }" X$ TOutliers, 极端值0 Y9 T- w( `- M2 T5 @
OVERALS , 多组变量的非线性正规相关 & M" D. v. h! {. a" b. I$ U; H
Overshoot, 迭代过度- \/ y& S9 b8 O& y- T" X" E: R6 }
Paired design, 配对设计- K. w9 l, w4 o# \# _
Paired sample, 配对样本
6 s% x' Z6 l+ A, i: k. D8 z- iPairwise slopes, 成对斜率
& z2 C# @9 M1 q" f: gParabola, 抛物线/ H) c0 B5 D0 R
Parallel tests, 平行试验
, j- Q* k0 _0 Z+ e! KParameter, 参数
9 [. X( Z0 ?& B7 H1 GParametric statistics, 参数统计! N, l7 e9 m& D# R- j0 \
Parametric test, 参数检验8 ]" g4 \& K9 F( ^; y0 `
Partial correlation, 偏相关
% \. Z! N6 y" o% _, o8 ]7 y2 @Partial regression, 偏回归2 o; G- A( o" @+ Z6 B
Partial sorting, 偏排序
* { E$ T, \& i6 s9 s6 P, G3 ^Partials residuals, 偏残差- v+ _/ j, Q H+ \! ^
Pattern, 模式
& I( p/ ^# t, `1 E/ APearson curves, 皮尔逊曲线) z8 S7 r9 U9 B: K" |$ e( i
Peeling, 退层
( O4 i& G( X u8 E( _Percent bar graph, 百分条形图: n, j5 n* [4 b' D: \
Percentage, 百分比' ^" r) D% k' V9 Q6 c- ^
Percentile, 百分位数 R- l! v; W1 R
Percentile curves, 百分位曲线2 `. x6 n+ n& ^8 r
Periodicity, 周期性5 w/ @& K7 e \- c
Permutation, 排列
/ I! S, Z; w1 F" ^' ~P-estimator, P估计量
; |9 \ }- I/ K# bPie graph, 饼图
7 Y; Q6 D6 q. TPitman estimator, 皮特曼估计量6 @8 p/ d- T) L) J8 n# I [: d
Pivot, 枢轴量
8 `7 v' {3 H$ b4 {& |3 B8 j1 dPlanar, 平坦2 c2 J8 @1 T0 j; E6 p( I3 @
Planar assumption, 平面的假设
/ _2 a, S: R: K; W5 xPLANCARDS, 生成试验的计划卡
+ B+ T( \( ~# }- CPoint estimation, 点估计
6 X! g1 Z1 l9 E$ U: GPoisson distribution, 泊松分布0 R/ h2 j! _, t# J. V
Polishing, 平滑
& C6 Q9 a$ \, [% OPolled standard deviation, 合并标准差
0 D G9 ?9 K& _+ T1 PPolled variance, 合并方差! a# E' E0 H0 M- K7 c
Polygon, 多边图
8 g( L" z2 v( ]; B1 E2 gPolynomial, 多项式/ C& H" c* x3 S1 }5 k
Polynomial curve, 多项式曲线$ ~8 d h( M# Y0 k: F
Population, 总体( w' N& H6 Z9 V
Population attributable risk, 人群归因危险度; N6 o* T0 W% i3 L2 a7 I
Positive correlation, 正相关
, R# W% i, U. y- M9 o; o) _. WPositively skewed, 正偏
. h0 B+ _$ B+ D- RPosterior distribution, 后验分布
/ Q+ f, c/ d6 [* g2 qPower of a test, 检验效能
* K/ |0 c8 o1 M9 l0 EPrecision, 精密度
4 b; I- D, g! k( ]Predicted value, 预测值+ h8 u( {; |) v- p
Preliminary analysis, 预备性分析
3 q' J4 `' A" o, rPrincipal component analysis, 主成分分析
3 P5 h" a4 k4 G& ]Prior distribution, 先验分布, _0 ]4 V$ k5 J( K$ i' r6 ~' P: B+ T: w
Prior probability, 先验概率
4 D9 s% r }' j' f5 y, G- D, dProbabilistic model, 概率模型( u1 k& Q6 _2 F# u" A
probability, 概率* X! r& w4 N& b& W1 A& K
Probability density, 概率密度
8 d& B: t. {* `8 BProduct moment, 乘积矩/协方差, c4 Z' ]0 g4 M8 W4 ^
Profile trace, 截面迹图
; \& {! d/ L6 K' m8 U: YProportion, 比/构成比
; S$ ~# o: ]- rProportion allocation in stratified random sampling, 按比例分层随机抽样6 f; p; B2 i$ ~% I
Proportionate, 成比例) I6 |5 l& }- `) n, K8 T6 V) E! d7 I
Proportionate sub-class numbers, 成比例次级组含量
7 }5 d3 F4 w, T, A7 zProspective study, 前瞻性调查
$ E' R0 u, \& O# T9 D, X% ^Proximities, 亲近性
4 ~3 f- s$ H' i2 |7 f3 `# RPseudo F test, 近似F检验: _8 g1 d. Z/ j9 \- s* j( V
Pseudo model, 近似模型
& B) G9 M. y+ Z1 y2 h* mPseudosigma, 伪标准差% B+ U1 q5 V9 O+ R
Purposive sampling, 有目的抽样
! {3 w1 }. F ~/ _3 o( E1 BQR decomposition, QR分解. U2 d$ m! I/ u$ h
Quadratic approximation, 二次近似/ W, z# h5 z# r- _: \3 D
Qualitative classification, 属性分类
+ T% F( S* n! U8 S' PQualitative method, 定性方法) h- t( w! K; U% u4 i" y$ e
Quantile-quantile plot, 分位数-分位数图/Q-Q图, p0 ~' F5 H& f% n3 `) [+ T# H7 O& u
Quantitative analysis, 定量分析
1 d: T- M' {5 v: O# a3 hQuartile, 四分位数
% F* h: L4 r5 Y( [2 E6 Y* }4 MQuick Cluster, 快速聚类
% y+ S. A4 t$ f+ X* ?$ BRadix sort, 基数排序# R( L% I7 S3 C7 K1 I9 U
Random allocation, 随机化分组
Z& L% X/ `) N8 ]Random blocks design, 随机区组设计
+ O5 C5 i9 n: ]+ l u3 f, e' mRandom event, 随机事件
; V1 D) S! n0 a/ BRandomization, 随机化
- A o3 W9 [$ wRange, 极差/全距
) V; @0 ~+ ?) U1 g( _2 x; c3 c5 WRank correlation, 等级相关
5 d! P$ x' Q, J9 k5 m7 SRank sum test, 秩和检验5 I. y1 Z1 y' m: P1 V
Rank test, 秩检验5 C) f6 |3 t9 |6 q5 ^
Ranked data, 等级资料1 p2 e& U1 S8 [. a- n
Rate, 比率# W+ B4 Y4 z+ x# E3 R
Ratio, 比例
( N- x7 w) S# b) M5 T6 \Raw data, 原始资料
1 {1 g/ ~! }$ i1 @Raw residual, 原始残差& ~' j( N, o* T! S/ b
Rayleigh's test, 雷氏检验3 b& H+ ~( U1 z: K
Rayleigh's Z, 雷氏Z值
9 c2 j5 v% {0 b3 e7 h( dReciprocal, 倒数( r9 h v$ ] p. U- G
Reciprocal transformation, 倒数变换
! R$ P/ Z5 S0 u7 M6 WRecording, 记录
( b# k( Q' |9 U+ l* M: B( y+ c2 s' i6 ` aRedescending estimators, 回降估计量- Y# S# m3 H! r q
Reducing dimensions, 降维2 _1 p6 e0 j& P. K/ y& Q! P0 c
Re-expression, 重新表达8 H3 d$ }3 F5 v I7 A* C$ _0 j& x
Reference set, 标准组
- F/ l, r* h( n; E6 dRegion of acceptance, 接受域+ U; h) _8 W9 M# k% Q
Regression coefficient, 回归系数9 e% `. h1 W& x0 Q
Regression sum of square, 回归平方和
# U# Q: `9 L: ^Rejection point, 拒绝点' t1 e8 p9 U3 g0 e3 {
Relative dispersion, 相对离散度7 x p9 H0 _+ }# @0 j2 t
Relative number, 相对数
3 f0 I( D3 E! `+ i ~Reliability, 可靠性& \. J6 t3 ^4 S* y {$ v" f7 a
Reparametrization, 重新设置参数/ R# h: @8 x$ f/ u( H
Replication, 重复
: g& Y% \/ j! j2 L, b% G) bReport Summaries, 报告摘要3 g0 K& ?$ G1 C" h' x1 [. J
Residual sum of square, 剩余平方和/ d1 F, ^7 j3 d
Resistance, 耐抗性+ s2 R" j, B/ b; a- W4 o
Resistant line, 耐抗线/ t) I s0 j" @$ K6 Z6 n
Resistant technique, 耐抗技术
2 B3 ^( T4 B+ \ q- p$ g) mR-estimator of location, 位置R估计量
3 s, r; u8 E/ G- t2 {" b, zR-estimator of scale, 尺度R估计量* G' z6 g3 [7 ` i7 C; b }0 D
Retrospective study, 回顾性调查8 }* K6 V' d1 S! I
Ridge trace, 岭迹
. I, [; u+ L' g/ ?& ~Ridit analysis, Ridit分析, {+ y/ T" Z' b+ {& ?0 [
Rotation, 旋转
3 ? R( t: ~, ERounding, 舍入
8 T) w( j8 o3 s, P# @) d gRow, 行
2 o! F a: L! R0 L7 v" `Row effects, 行效应
0 l# B' {0 t7 R% {Row factor, 行因素' l4 a0 U8 I7 q5 I
RXC table, RXC表
: |* ^8 z& }4 u+ D% r) VSample, 样本
% k+ o5 H4 e& K) q' Q! ?Sample regression coefficient, 样本回归系数; |/ I! |6 F0 K' G
Sample size, 样本量' W0 U* b; C" F1 f
Sample standard deviation, 样本标准差
8 O3 ?' L1 J/ J! MSampling error, 抽样误差& m2 v* c6 P0 o+ O
SAS(Statistical analysis system ), SAS统计软件包; t* G0 E8 n0 W7 _; i( Z* K
Scale, 尺度/量表
( t$ n$ d0 w+ i$ mScatter diagram, 散点图
, o6 ^' G, l/ c' {. B, HSchematic plot, 示意图/简图8 x( v0 e; ?+ V' h" m1 B
Score test, 计分检验
" I' \+ |* z. h' aScreening, 筛检) P0 E" j5 _ s. i
SEASON, 季节分析 . o, w6 z% h! E
Second derivative, 二阶导数
' O% E' X( c. _4 x; U- |Second principal component, 第二主成分) r" J4 J/ ?6 X; i5 }* C
SEM (Structural equation modeling), 结构化方程模型 , p( ?' O! ]# Y! S9 ~$ D5 [1 s+ p
Semi-logarithmic graph, 半对数图- ?( {' d$ Y- e) L5 s9 |
Semi-logarithmic paper, 半对数格纸
% Q) c* | N% x; l" b7 W( \Sensitivity curve, 敏感度曲线
3 q0 M& c$ y4 n+ r8 w% p1 j6 N/ mSequential analysis, 贯序分析# i# f' n; K `; _) S( E! o( Z
Sequential data set, 顺序数据集
5 U. `8 @- r/ [* P* o& {% PSequential design, 贯序设计
1 W R; {$ }" N) ]Sequential method, 贯序法
4 o/ j7 L. w, `0 r8 Q) uSequential test, 贯序检验法# Q3 K' o, r* `% y6 V/ F
Serial tests, 系列试验
8 S# h2 A4 B# g, c) oShort-cut method, 简捷法
8 {, B1 [* R( |4 t5 S# d* rSigmoid curve, S形曲线' l- j7 j7 @; _# g+ W
Sign function, 正负号函数
6 F. N- \4 u" g! \' A) A# e/ ?7 SSign test, 符号检验, X8 r a, S5 b$ r
Signed rank, 符号秩; l% G2 u0 H$ s; n
Significance test, 显著性检验! t, }) T; U# r2 p- c
Significant figure, 有效数字
" x! O. M( P- O# {) y; nSimple cluster sampling, 简单整群抽样, y; ~8 t2 Z' \+ Y; |0 E/ f
Simple correlation, 简单相关
, S% P7 E+ f) b! y9 ySimple random sampling, 简单随机抽样. h; [. ]5 N5 p; h; n+ s
Simple regression, 简单回归
* C+ s4 O% f/ h7 Osimple table, 简单表
5 V: m2 Z. P% x8 q+ XSine estimator, 正弦估计量
' o6 T2 ]6 B' P2 S* R3 VSingle-valued estimate, 单值估计
: j3 V8 Z9 Y, ]8 o1 j$ m& QSingular matrix, 奇异矩阵 ?& ?9 l" |( z3 c# K/ K" _+ v
Skewed distribution, 偏斜分布+ S9 v+ o0 M' ]
Skewness, 偏度
6 `2 l/ L$ H- s3 Q! U* G* KSlash distribution, 斜线分布9 C ?- Y+ n! u2 x# e) u* {: X9 n, P
Slope, 斜率0 C# n& n9 @7 \# ]/ T
Smirnov test, 斯米尔诺夫检验
# d/ I: _! g' D; i9 LSource of variation, 变异来源
- z4 ^( D" N! R3 |% ?6 e# }Spearman rank correlation, 斯皮尔曼等级相关
! {% Q4 L7 O0 SSpecific factor, 特殊因子
: C ~) D! ~' F ~6 X+ YSpecific factor variance, 特殊因子方差
# j2 [/ W5 O M# F0 w) K" JSpectra , 频谱% e* g: B* i5 r/ H4 m' {9 {* I
Spherical distribution, 球型正态分布
% D. f6 P+ V9 B" H+ h2 |0 lSpread, 展布# w( W0 ^/ _" a# r2 i% g
SPSS(Statistical package for the social science), SPSS统计软件包
- X1 K' I5 b2 z7 j H" ]; M$ n9 G( i( SSpurious correlation, 假性相关
2 E6 k4 i5 G O/ q4 jSquare root transformation, 平方根变换
; _( T# f6 M" g& A5 t# [( ^Stabilizing variance, 稳定方差
8 g* i+ u9 ^9 \. TStandard deviation, 标准差
~ K+ C6 `- k6 @; v8 SStandard error, 标准误7 H4 @6 m" H. _2 @
Standard error of difference, 差别的标准误
d; L6 ^7 B+ M; SStandard error of estimate, 标准估计误差
" l! L$ K2 k8 g( \( ]8 q& {) xStandard error of rate, 率的标准误5 T3 Z& Z. u* m) T' O/ y' e" b
Standard normal distribution, 标准正态分布
8 v0 B- C" \% m: T2 F! ]7 y# w; QStandardization, 标准化
5 k! ~3 V. g# c' F% R* CStarting value, 起始值
: W- ? H* Q, t+ r! ]! ZStatistic, 统计量
3 M9 m1 L, C, }$ T8 y5 ]# tStatistical control, 统计控制
* E+ Z! ?0 X: ^- o/ R" ` dStatistical graph, 统计图
5 t/ }) u c% D- O) Q5 lStatistical inference, 统计推断
/ y& n t! a4 eStatistical table, 统计表) S- J' z O7 g! X6 n
Steepest descent, 最速下降法8 @' M: C* P+ o: I* T
Stem and leaf display, 茎叶图
3 b" t$ t3 O) }3 T& X6 Z7 ^Step factor, 步长因子
, c- B' ~+ r& O( p! L5 XStepwise regression, 逐步回归
# w F7 d) @3 T4 ~Storage, 存- o6 R4 v0 I3 p# o
Strata, 层（复数）
- C4 R2 ~# B# D9 f7 ~5 F' n3 FStratified sampling, 分层抽样
( c. l& i+ N8 m/ t) GStratified sampling, 分层抽样
; q1 ~# s/ h$ X! J# ^% A$ cStrength, 强度6 w2 X7 J \2 c/ L+ v3 T
Stringency, 严密性
& C4 k; ^; ^9 W; H. k; aStructural relationship, 结构关系8 \& c6 }) X0 n: y1 Y( t& k% H
Studentized residual, 学生化残差/t化残差9 F6 S9 p# B2 |/ m" b! G' K4 m( _
Sub-class numbers, 次级组含量
7 c8 T! W) E, I: E' rSubdividing, 分割
/ H5 n( M, m8 }6 ]Sufficient statistic, 充分统计量
- R x8 o/ W/ P6 hSum of products, 积和
( \# b1 J- D$ {, PSum of squares, 离差平方和: `5 l* q" `' ~: P$ @7 }/ h. k
Sum of squares about regression, 回归平方和1 s% V8 h3 ^9 a' P
Sum of squares between groups, 组间平方和6 M8 O" b3 u) c! T1 J
Sum of squares of partial regression, 偏回归平方和
. r" `# g0 M7 a1 s6 A( gSure event, 必然事件
, W1 F4 M+ _! aSurvey, 调查4 [) J5 m$ R9 n. r: ~2 O5 y& d
Survival, 生存分析
( A. F/ K) f" \' X2 ^1 \/ ?% ]/ jSurvival rate, 生存率
3 u/ v5 O: L/ A. w. e" Q& \" }Suspended root gram, 悬吊根图
" D% t: G& }) V' DSymmetry, 对称
& D# A2 ?$ W( m5 q& {Systematic error, 系统误差- H: P% C% {4 s. s; `
Systematic sampling, 系统抽样
. N/ p. u- N' n2 ^$ @# N2 [- ?Tags, 标签! Q' M# ^# R4 c3 ]6 C8 ^, K9 I. P
Tail area, 尾部面积) q% C; S7 R6 V F4 H
Tail length, 尾长9 b* y( \' n4 ^3 a. z' s' V
Tail weight, 尾重6 [2 z# t6 t0 L+ t f# T( M
Tangent line, 切线3 \* C% ~; ]3 s2 R2 q6 _
Target distribution, 目标分布
; o' o, b6 C* n9 N! F! TTaylor series, 泰勒级数8 x6 a& m3 A; z' i
Tendency of dispersion, 离散趋势
* o3 b9 i7 S! j( p3 t' C% VTesting of hypotheses, 假设检验
) _0 I7 B5 u( c1 k# ~1 mTheoretical frequency, 理论频数
' e- K# x U! X1 z7 v- j& `/ ZTime series, 时间序列
& j5 z, }! G9 hTolerance interval, 容忍区间
' T9 A5 a. m2 p1 pTolerance lower limit, 容忍下限! [' H% S' {+ c- z/ X6 C* @. b0 o/ m b
Tolerance upper limit, 容忍上限
( m6 v Y/ s* t/ lTorsion, 扰率2 |+ w D2 @' g! V# |
Total sum of square, 总平方和
* |1 B% C( @6 u# L- x( mTotal variation, 总变异
2 P8 Q+ N# I: ]+ J: Z8 h0 M4 iTransformation, 转换2 ?( w4 s* B& D4 P1 M/ O
Treatment, 处理6 c3 j% _. g* y$ \1 x( T
Trend, 趋势
. S! B4 R, l0 y! X7 }+ q8 MTrend of percentage, 百分比趋势
7 ?& G4 ]7 \2 U: { |Trial, 试验3 y! ^& @( n1 E
Trial and error method, 试错法
6 U- ^* ^& f( _% ~Tuning constant, 细调常数
: Y) E6 B/ n8 k$ s/ `5 PTwo sided test, 双向检验, a4 j! Z. @+ ^& W+ L8 _
Two-stage least squares, 二阶最小平方
& a8 p; J, ^" q" k rTwo-stage sampling, 二阶段抽样
4 X5 ~2 k. c6 _% ?Two-tailed test, 双侧检验; G* l* r, G+ z8 g
Two-way analysis of variance, 双因素方差分析
3 }, O! o* [% F9 ETwo-way table, 双向表
* b. ]0 y3 h( m6 S% j/ U5 O4 T$ eType I error, 一类错误/α错误7 o/ O3 W. P. y3 u: b$ _: N3 R
Type II error, 二类错误/β错误9 ?* W# y0 |& Y$ Q' f: |. D) l
UMVU, 方差一致最小无偏估计简称
$ @ G% L/ J* \4 [1 I+ CUnbiased estimate, 无偏估计, g' e7 j9 Z. [/ v$ j. v4 |* T
Unconstrained nonlinear regression , 无约束非线性回归" ?6 Q; o3 }0 M L: |2 ]
Unequal subclass number, 不等次级组含量
% P9 N3 ^: Z4 |; h) \% V0 rUngrouped data, 不分组资料
% O! v: R2 i( J6 }# i9 PUniform coordinate, 均匀坐标2 G, c% X' O! e8 B" L
Uniform distribution, 均匀分布7 n+ h% m- v" L* a$ M
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计5 q) g8 B9 m& d+ W% P4 S
Unit, 单元
- q5 F4 |/ X# p% x/ RUnordered categories, 无序分类
9 P5 @! F( F6 A7 P$ M: D4 TUpper limit, 上限
" f1 P; d) l7 A5 BUpward rank, 升秩
+ H" b" z2 p7 o9 c8 PVague concept, 模糊概念3 R! T$ x5 I- m! n5 T/ _# L
Validity, 有效性
! F5 L) F2 h0 w# UVARCOMP (Variance component estimation), 方差元素估计
; [' [* V. t. y0 H) GVariability, 变异性3 K' g/ i/ [# L }5 E/ @
Variable, 变量3 v/ J& y3 v0 Q3 C8 f7 q
Variance, 方差8 G9 n# X# [! |' C/ U
Variation, 变异
8 ?( B# |/ }% @Varimax orthogonal rotation, 方差最大正交旋转
7 \: ?3 t* m8 v- o6 e W1 FVolume of distribution, 容积
1 S% x* N' z' C) v! s/ AW test, W检验
' ~7 T$ p# Y, {) L! v. N9 aWeibull distribution, 威布尔分布
$ \7 e# e0 o& _; E2 rWeight, 权数% t* g$ X) g7 ^( H! l! u
Weighted Chi-square test, 加权卡方检验/Cochran检验+ R0 p. Q8 m; ~9 P9 S( `
Weighted linear regression method, 加权直线回归
% w0 s4 c) ~) F* r9 NWeighted mean, 加权平均数( ~6 ~# x# d. J1 Q3 M
Weighted mean square, 加权平均方差+ }1 t1 K& K, h3 i8 @8 s
Weighted sum of square, 加权平方和
( d0 w# d! ]# X3 j* y+ o; t7 UWeighting coefficient, 权重系数
0 ~ W- Q$ U5 U; E! ]$ [* sWeighting method, 加权法
% w+ D% }. X0 p3 C) HW-estimation, W估计量
- r6 U& Z1 e P* O3 JW-estimation of location, 位置W估计量- E% b! A" T6 s; A
Width, 宽度
4 _+ w8 j4 i- \4 O5 TWilcoxon paired test, 威斯康星配对法/配对符号秩和检验/ c9 L3 l- w. b6 L0 c& \9 m0 ]
Wild point, 野点/狂点
& K- H! o) \- H/ X1 O, g! d& fWild value, 野值/狂值
. M& m. B/ G" }( UWinsorized mean, 缩尾均值
5 J4 E1 x' a7 kWithdraw, 失访 1 e7 m' l% Q) n9 e
Youden's index, 尤登指数1 v( k/ T3 Z! m
Z test, Z检验
+ `# M% n, \1 F5 `& rZero correlation, 零相关
* `+ n+ w: z( g8 m1 IZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
